1. Field of the Disclosure
The disclosure relates to an image processing method and an image processing device. Particularly, the disclosure relates to an image stabilization method and an image stabilization device.
2. Description of Related Art
As video cameras are extensively set up in recent years, in addition to the use of monitoring systems, the video cameras are widely used in mobile carriers such as vehicles or airplanes, etc. Whatever the application domain is, the video camera is exposed in an environment that is liable to be influenced by external factors, for example, shaking of occasional wind or shaking of the mobile carrier itself may all influence images captured by the video camera, and further influence a subsequent image analysis performance, so that image stabilization gradually becomes an important issue in the image processing technique.
Based on different set up environments, the video cameras generally include fixed video cameras and mobile video cameras. Image stabilization of the fixed video camera is generally implemented by simply comparing a foreground with a background to remove a motion appeared in the foreground, i.e. to achieve a full stop effect. However, the mobile video camera generally moves along a smooth trajectory, and the smooth trajectory is a moving trajectory to be maintained, which cannot be removed. Therefore, regarding image stabilization of the mobile video camera, it is a key issue to separate a motion of the unknown smooth trajectory and a motion of a shaking component in the image.
According to different motion models (for example, a difference between a vehicle and an airplane), a most suitable model is selected in advance. And a smooth degree and an approximation degree have to be considered in selection of the motion model and parameters. Therefore, how to select a suitable model and adjust parameters of the smooth trajectory degree and the approximation degree are required to be resolved.
The second method for estimating the smooth trajectory is to use a Kalman filter to approximate the observed un-smooth trajectory, and use the characteristics of past data points to estimate the characteristics of future data points. In other words, a trajectory of the past data points is used to estimate a future possible smooth trajectory, and remove the shaking component other than the smooth trajectory.
The third method for estimating the smooth trajectory is a foreground removal method, by which image content is analyzed to separate a foreground motion and a background motion. Such method requires further computation on the image content. Moreover applicability of the method is required to deal that the foreground motion and the background motion be clearly separated in case the background is shaken violently.
Therefore, it is desirable required to develop an image stabilization method and an image stabilization device capable of finding a suitable smooth trajectory of the video camera and removing shaking components caused by external factors such as wind blowing and handshaking, etc.